The World Meteorological Organization (WMO) has launched a new pilot project in Malawi, in partnership with the meteorological services of Norway and Malawi, to explore how artificial intelligence (AI) can enhance weather forecasting and early warning systems in resource-limited settings.
The project, backed by funding from the Climate Risk and Early Warning Systems (CREWS) initiative, introduces a state-of-the-art AI-based Weather Prediction (AI-WP) system in Malawi. It aims to improve the accuracy, timeliness, and accessibility of forecasts while building local capacity within the Department of Climate Change and Meteorological Services (DCCMS).
Malawi is highly vulnerable to climate-related hazards but lacks advanced forecasting infrastructure.
This AI initiative seeks to close critical capability gaps using innovative tools like: Bris, a high-resolution, data-driven forecasting model developed by MET-Norway, Forecast-in-a-Box, a compact forecasting solution by the European Centre for Medium-Range Weather Forecasts (ECMWF), as part of its Digital Twin Engine and Destination Earth initiatives.
These AI models are lightweight and portable, designed to run without access to supercomputers.
They allow forecasters to: tailor prediction systems to local needs, deploy models closer to where data is collected and improve responsiveness without requiring deep technical expertise.
“This project represents a strategic opportunity to strengthen Malawi’s early warning infrastructure and support long-term development of our forecasting staff,” said Dr. Lucy Mtilatila, Malawi’s Permanent Representative to the WMO.
The initiative is part of WMO’s broader effort to help Least Developed Countries (LDCs) and Small Island Developing States (SIDS) leapfrog to next-generation weather prediction systems.
It also reflects the WMO Executive Council’s growing focus on AI, including the creation of a Joint Advisory Council on Artificial Intelligence.
WMO is now working on technical guidelines to integrate AI models into its Integrated Processing and Prediction System (WIPPS), the global forecasting backbone used by national meteorological services.
While the promise is clear, WMO acknowledges that open questions remain about AI’s ability to deliver reliable local-scale forecasts, especially for high-impact weather and water events.
The pilot in Malawi will help evaluate those capabilities in real-world conditions.
“This project represents a strategic opportunity to strengthen Malawi’s early warning infrastructure.”
Dr. Lucy Mtilatila
Malawi’s Permanent Representative to the WMO
